| KEYWORD |
Reliability System Optmizer
keywords GENETIC ALGORITHMS, COMBINATORIAL OPTIMIZATION, MATHEMATICAL MODELING, STATISTICS
Reference persons STEFANO DI CARLO
External reference persons Alessandro Savino - alessandro.savino@polito.it
Research Groups TESTGROUP - TESTGROUP
Thesis type RESEARCH, INNOVATIVE
Description Modern microprocessor systems require a reduced time-to-market that makes all projects keen on post-production errors and failures. They simply cannot be tested enough so designer do not know their reliability anymore. We can cope with that! We statistically evaluate the project at very early-stages, long before going to production, knowing how and where something might go wrong. But we want to do even more!
All possible alternatives to the current system design can be analyzed in terms of reliability to solve the problem. Imagine to be suggested on what you can improve in your systems design the same fashioned way Google understands your thought when you are still digitizing your words to be searched on its website. We believe that Extremal optimization techniques will serve the purpose.
During the thesis the candidate will be immerse in a very stimulating research environment, learning and experimenting Genetic Algorithms (GA) and Extremal Optimization (EO) techniques, as well as statistical models and very advanced programming. Enthusiastic students will also have the possibility to challenge themselves with some Graphical User Interface (GUI) concepts.
Required skills C/C++
Deadline 10/09/2016
PROPONI LA TUA CANDIDATURA